Localisation d'ARN non-codants par réseaux de contraintes pondérées

Alternative Title

Sequence kernels for speaker verification using support vector machines (SVM)

Abstract

Following recent discoveries about the several roles of non-coding RNAs (ncRNAs), there is now great interest in identifying these molecules. Numerous techniques have been developed to localize these RNAs in genomic sequences. We use here an approach which supposes the knowledge of a set of structural elements called signature that discriminate an ncRNA family. In this work, we combine several pattern-matching techniques with the weighted constraint satisfaction problem framework. Together, they make it possible to model our biological problem, to describe accurately the signatures and to give the solutions a cost. We conceived filtering techniques as well as novel pattern-matching algorithms. Furthermore, we designed a software called DARN! that implements our approach and another tool that automatically creates signatures. These tools make it possible to localize efficiently new ncRNAs.